Packages

class DoubleMLModel extends Model[DoubleMLModel] with DoubleMLParams with ComplexParamsWritable with Wrappable with SynapseMLLogging

Model produced by DoubleMLEstimator.

Linear Supertypes
SynapseMLLogging, Wrappable, DotnetWrappable, RWrappable, PythonWrappable, BaseWrappable, ComplexParamsWritable, MLWritable, DoubleMLParams, HasParallelismInjected, HasParallelism, HasWeightCol, HasMaxIter, HasFeaturesCol, HasOutcomeCol, HasTreatmentCol, Model[DoubleMLModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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  2. By Inheritance
Inherited
  1. DoubleMLModel
  2. SynapseMLLogging
  3. Wrappable
  4. DotnetWrappable
  5. RWrappable
  6. PythonWrappable
  7. BaseWrappable
  8. ComplexParamsWritable
  9. MLWritable
  10. DoubleMLParams
  11. HasParallelismInjected
  12. HasParallelism
  13. HasWeightCol
  14. HasMaxIter
  15. HasFeaturesCol
  16. HasOutcomeCol
  17. HasTreatmentCol
  18. Model
  19. Transformer
  20. PipelineStage
  21. Logging
  22. Params
  23. Serializable
  24. Serializable
  25. Identifiable
  26. AnyRef
  27. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new DoubleMLModel()
  2. new DoubleMLModel(uid: String)

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. def awaitFutures[T](futures: Array[Future[T]]): Seq[T]
    Attributes
    protected
    Definition Classes
    HasParallelismInjected
  7. lazy val classNameHelper: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  8. final def clear(param: Param[_]): DoubleMLModel.this.type
    Definition Classes
    Params
  9. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  10. def companionModelClassName: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  11. val confidenceLevel: DoubleParam
    Definition Classes
    DoubleMLParams
  12. def copy(extra: ParamMap): DoubleMLModel
    Definition Classes
    DoubleMLModel → Model → Transformer → PipelineStage → Params
  13. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  14. lazy val copyrightLines: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  15. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  16. def dotnetAdditionalMethods: String
    Definition Classes
    DotnetWrappable
  17. def dotnetClass(): String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  18. lazy val dotnetClassName: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  19. lazy val dotnetClassNameString: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  20. lazy val dotnetClassWrapperName: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  21. lazy val dotnetCopyrightLines: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  22. def dotnetExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  23. def dotnetExtraMethods: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  24. lazy val dotnetInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  25. def dotnetMLReadWriteMethods: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  26. lazy val dotnetNamespace: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  27. lazy val dotnetObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  28. def dotnetParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  29. def dotnetParamGetters: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  30. def dotnetParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  31. def dotnetParamSetters: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  32. def dotnetWrapAsTypeMethod: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  33. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  34. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  35. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  36. def explainParams(): String
    Definition Classes
    Params
  37. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  38. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  39. val featuresCol: Param[String]

    The name of the features column

    The name of the features column

    Definition Classes
    HasFeaturesCol
  40. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  41. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  42. def getAvgTreatmentEffect: Double
  43. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  44. def getConfidenceInterval: Array[Double]
  45. def getConfidenceLevel: Double
    Definition Classes
    DoubleMLParams
  46. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  47. def getExecutionContextProxy: ExecutionContext
    Definition Classes
    HasParallelismInjected
  48. def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol
  49. final def getMaxIter: Int
    Definition Classes
    HasMaxIter
  50. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  51. def getOutcomeCol: String
    Definition Classes
    HasOutcomeCol
  52. def getOutcomeModel: Estimator[_ <: Model[_]]
    Definition Classes
    DoubleMLParams
  53. def getParallelism: Int
    Definition Classes
    HasParallelism
  54. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  55. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  56. def getRawTreatmentEffects: Array[Double]
  57. def getSampleSplitRatio: Array[Double]
    Definition Classes
    DoubleMLParams
  58. def getTreatmentCol: String
    Definition Classes
    HasTreatmentCol
  59. def getTreatmentModel: Estimator[_ <: Model[_]]
    Definition Classes
    DoubleMLParams
  60. def getWeightCol: String

    Definition Classes
    HasWeightCol
  61. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  62. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  63. def hasParent: Boolean
    Definition Classes
    Model
  64. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  65. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  66. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  67. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  68. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  69. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  70. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  71. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  72. def logBase(info: SynapseMLLogInfo): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  73. def logBase(methodName: String): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  74. def logClass(): Unit
    Definition Classes
    SynapseMLLogging
  75. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  76. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  77. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  78. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. def logErrorBase(methodName: String, e: Exception): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  80. def logFit[T](f: ⇒ T): T
    Definition Classes
    SynapseMLLogging
  81. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  82. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  83. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  84. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  85. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  86. def logTrain[T](f: ⇒ T): T
    Definition Classes
    SynapseMLLogging
  87. def logTransform[T](f: ⇒ T): T
    Definition Classes
    SynapseMLLogging
  88. def logVerb[T](verb: String, f: ⇒ T): T
    Definition Classes
    SynapseMLLogging
  89. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  90. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  91. def makeDotnetFile(conf: CodegenConfig): Unit
    Definition Classes
    DotnetWrappable
  92. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  93. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  94. final val maxIter: IntParam
    Definition Classes
    HasMaxIter
  95. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  96. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  97. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  98. val outcomeCol: Param[String]
    Definition Classes
    HasOutcomeCol
  99. val outcomeModel: EstimatorParam
    Definition Classes
    DoubleMLParams
  100. val parallelism: IntParam
    Definition Classes
    HasParallelism
  101. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  102. var parent: Estimator[DoubleMLModel]
    Definition Classes
    Model
  103. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  104. lazy val pyClassDoc: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  105. lazy val pyClassName: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  106. def pyExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  107. def pyExtraEstimatorMethods: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  108. lazy val pyInheritedClasses: Seq[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  109. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  110. lazy val pyInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    DoubleMLModelPythonWrappable
  111. lazy val pyObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  112. def pyParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  113. def pyParamDefault[T](p: Param[T]): Option[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  114. def pyParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  115. def pyParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  116. def pyParamsArgs: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  117. def pyParamsDefaults: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  118. lazy val pyParamsDefinitions: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  119. def pyParamsGetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  120. def pyParamsSetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  121. def pythonClass(): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  122. def rClass(): String
    Attributes
    protected
    Definition Classes
    RWrappable
  123. def rDocString: String
    Attributes
    protected
    Definition Classes
    RWrappable
  124. def rExtraBodyLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  125. def rExtraInitLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  126. lazy val rFuncName: String
    Attributes
    protected
    Definition Classes
    RWrappable
  127. lazy val rInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    RWrappable
  128. def rParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    RWrappable
  129. def rParamsArgs: String
    Attributes
    protected
    Definition Classes
    RWrappable
  130. def rSetterLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  131. val rawTreatmentEffects: DoubleArrayParam
  132. val sampleSplitRatio: DoubleArrayParam
    Definition Classes
    DoubleMLParams
  133. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  134. final def set(paramPair: ParamPair[_]): DoubleMLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  135. final def set(param: String, value: Any): DoubleMLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  136. final def set[T](param: Param[T], value: T): DoubleMLModel.this.type
    Definition Classes
    Params
  137. def setConfidenceLevel(value: Double): DoubleMLModel.this.type

    Set the higher bound percentile of ATE distribution.

    Set the higher bound percentile of ATE distribution. Default is 0.975. lower bound value will be automatically calculated as 100*(1-confidenceLevel) That means by default we compute 95% confidence interval, it is [2.5%, 97.5%] percentile of ATE distribution

    Definition Classes
    DoubleMLParams
  138. final def setDefault(paramPairs: ParamPair[_]*): DoubleMLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  139. final def setDefault[T](param: Param[T], value: T): DoubleMLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  140. def setFeaturesCol(value: String): DoubleMLModel.this.type

    Definition Classes
    HasFeaturesCol
  141. def setMaxIter(value: Int): DoubleMLModel.this.type

    Set the maximum number of confidence interval bootstrapping iterations.

    Set the maximum number of confidence interval bootstrapping iterations. Default is 1, which means it does not calculate confidence interval. To get Ci values please set a meaningful value

    Definition Classes
    DoubleMLParams
  142. def setOutcomeCol(value: String): DoubleMLModel.this.type

    Set name of the column which will be used as outcome

    Set name of the column which will be used as outcome

    Definition Classes
    HasOutcomeCol
  143. def setOutcomeModel(value: Estimator[_ <: Model[_]]): DoubleMLModel.this.type

    Set outcome model, it could be any model derived from 'org.apache.spark.ml.regression.Regressor' or 'org.apache.spark.ml.classification.ProbabilisticClassifier'

    Set outcome model, it could be any model derived from 'org.apache.spark.ml.regression.Regressor' or 'org.apache.spark.ml.classification.ProbabilisticClassifier'

    Definition Classes
    DoubleMLParams
  144. def setParallelism(value: Int): DoubleMLModel.this.type
    Definition Classes
    DoubleMLParams
  145. def setParent(parent: Estimator[DoubleMLModel]): DoubleMLModel
    Definition Classes
    Model
  146. def setRawTreatmentEffects(v: Array[Double]): DoubleMLModel.this.type
  147. def setSampleSplitRatio(value: Array[Double]): DoubleMLModel.this.type

    Set the sample split ratio, default is Array(0.5, 0.5)

    Set the sample split ratio, default is Array(0.5, 0.5)

    Definition Classes
    DoubleMLParams
  148. def setTreatmentCol(value: String): DoubleMLModel.this.type

    Set name of the column which will be used as treatment

    Set name of the column which will be used as treatment

    Definition Classes
    HasTreatmentCol
  149. def setTreatmentModel(value: Estimator[_ <: Model[_]]): DoubleMLModel.this.type

    Set treatment model, it could be any model derived from 'org.apache.spark.ml.regression.Regressor' or 'org.apache.spark.ml.classification.ProbabilisticClassifier'

    Set treatment model, it could be any model derived from 'org.apache.spark.ml.regression.Regressor' or 'org.apache.spark.ml.classification.ProbabilisticClassifier'

    Definition Classes
    DoubleMLParams
  150. def setWeightCol(value: String): DoubleMLModel.this.type

    Definition Classes
    HasWeightCol
  151. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  152. val thisStage: Params
    Attributes
    protected
    Definition Classes
    BaseWrappable
  153. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  154. def transform(dataset: Dataset[_]): DataFrame

    :: Experimental :: DoubleMLEstimator transform function is still experimental, and its behavior could change in the future.

    :: Experimental :: DoubleMLEstimator transform function is still experimental, and its behavior could change in the future.

    Definition Classes
    DoubleMLModel → Transformer
    Annotations
    @Experimental()
  155. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  156. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  157. def transformSchema(schema: StructType): StructType
    Definition Classes
    DoubleMLModel → PipelineStage
    Annotations
    @DeveloperApi()
  158. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  159. val treatmentCol: Param[String]
    Definition Classes
    HasTreatmentCol
  160. val treatmentModel: EstimatorParam
    Definition Classes
    DoubleMLParams
  161. val uid: String
    Definition Classes
    DoubleMLModelSynapseMLLogging → Identifiable
  162. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  163. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  164. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  165. val weightCol: Param[String]

    The name of the weight column

    The name of the weight column

    Definition Classes
    HasWeightCol
  166. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable

Inherited from SynapseMLLogging

Inherited from Wrappable

Inherited from DotnetWrappable

Inherited from RWrappable

Inherited from PythonWrappable

Inherited from BaseWrappable

Inherited from ComplexParamsWritable

Inherited from MLWritable

Inherited from DoubleMLParams

Inherited from HasParallelismInjected

Inherited from HasParallelism

Inherited from HasWeightCol

Inherited from HasMaxIter

Inherited from HasFeaturesCol

Inherited from HasOutcomeCol

Inherited from HasTreatmentCol

Inherited from Model[DoubleMLModel]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

getParam

param

setParam

Ungrouped